Breast cancer is the most widespread cancer in women and young women worldwide. Moving towards customised radiotherapy, balancing the use of the available technology with the best treatment modality may not be an easy task in the daily routine. This study aims to evaluate the effectiveness of introducing IQ-feasibility into clinical practice to support the decision of free-breathing (FB) versus breath-hold (BH) left-sided breast irradiations, in order to optimise the technology available and the effectiveness of the treatment.Thirty-five patients who received 3D radiotherapy treatment of the left breast in deep-inspiration BH were included in this retrospective study. Computed tomography scans in FB and BH were acquired for each patient; targets contoured in both imaging datasets by an experienced radiation oncologist, and organs at risk delineated using automatic segmentation software were exported to PlanIQ™ (Sun Nuclear Corp.) to generate feasibility dose volume histogram (FDVHs). The dosimetric parameter of BH versus FB FDVH, and BH clinical dataset versus BH FDVH were compared.A total of 30 patients out of 35 patients analysed, presented for the BH treatments a significant reduction (p < 0.05) in the heart mean dose ([Formula: see text]), volume receiving 5 Gy ([Formula: see text]) and 20 Gy ([Formula: see text]), of 35.7%, 54.5%, and 2.1%, respectively; for the left lung, a lower reduction was registered and significant only for [Formula: see text] (21.4%, p = 0.046). For the remaining five patients, the FDVH cut-off points of heart and lung were superimposable with differences of less than 1%. Heart and left lung dosimetric parameters of the BH clinical plans are located in the difficult zone of the FDVH and differ significantly (p < 0.05) from the corresponding parameters of the FDVH curves delimiting this buffer area between the impossible and feasible zones, respectively.The use of PlanIQTM as a decision-support tool for the FB versus BH treatment delivery modality allows customisation of the treatment technique using the most appropriate technology for each patient enabling accurate management of available technologies.© 2023. The Author(s).